Deep learning : a practitioner's approach /

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How can machine learning--especially deep neural networks--make a real difference in your organization? This hands-on guide not only provides practical information, but helps you get started building efficient deep learning networks. The authors provide the fundamentals of deep learning--tuning, par...

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Bibliographic Details
Call Number:Libro Electrónico
Main Authors: Patterson, Josh (Consultant) (Author), Gibson, Adam, 1989- (Author)
Format: Electronic eBook
Language:Inglés
Published: Sebastopol, CA : O'Reilly Media, Inc., 2017.
Edition:First edition.
Subjects:
Machine learning.
Artificial intelligence.
Neural networks (Computer science)
Artificial Intelligence
Neural Networks, Computer
Apprentissage automatique.
Intelligence artificielle.
Réseaux neuronaux (Informatique)
artificial intelligence.
COMPUTERS > General.
Online Access:Texto completo (Requiere registro previo con correo institucional)
Table of Contents:
  • A review of machine learning
  • Foundations of neural networks and deep learning
  • Fundamentals of deep networks
  • Major architecture of deep networks
  • Building deep networks
  • Tuning deep networks
  • Tuning specific deep network architectures
  • Vectorization
  • Using deep learning and DL4J on Spark
  • What is artificial intelligence?
  • RL4J and reinforcement learning
  • Numbers everyone should know
  • Neural networks and backpropagation: a mathematical approach
  • Using the ND4J API
  • Using DataVec
  • Working with DL4J from source
  • Setting up DL4J projects
  • Setting up GPUs for DL4J projects
  • Troubleshooting DL4J installations.

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